Cloninger's psychobiological model of personality and psychological distress in fibromyalgia
Bibliographic record
Abstract
AIM: Personality can play an important role in the clinical symptoms of fibromyalgia (FM). The aim of this study is to identify personality profiles in FM patients and the possible presence of personality disorder (PD) from the Temperament and Character Inventory-Revised (TCI-R), and to assess whether personality dimensions are related to psychological distress in FM. METHOD: The sample consisted of 42 patients with FM and 38 healthy controls. The TCI-R, Hospital Anxiety and Depression Scale, State-Trait Anxiety Inventory, Short-Form-36 Health Survey, Fibromyalgia Impact Questionnaire and McGill Pain Questionnaire were administered. RESULTS: The personality profile of the FM group based on the TCI-R is defined by high Harm Avoidance (HA), low Novelty Seeking (NS), and low Self-Directedness (SD). Only one-third of patients with FM present a possible psychometric PD, principally from Cluster C. In the FM group, HA and SD are associated positively and negatively, respectively, with indicators of emotional distress. Patients with higher HA present higher perceived pain intensity rated via a verbal-numerical scale while Determination (SD2) reduced the perceived level of pain induced by the stimulus. NS is negatively related to the number of work absences caused by FM. CONCLUSIONS: The study suggests that HA and SD play an important role in psychological distress in FM. The fact that SD is prone to modification and has a regulatory effect on emotional impulses is a key aspect to consider from the psychotherapeutic point of view.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".